Seminars

The CCIB seminar series offers interesting presentations related to research in computational and integrative biology. The presentations reflect the types of collaborative research being done at the center and provide an opportunity to come together as a community for informal discussions and conversation.

Unless noted, all seminars take place during the free period (12:20pm – 1:20pm) in Armitage Hall, 3rd Floor Faculty Lounge.

Coffee and snacks are provided.

2013-2014 Seminars:

Tejashree Redij

Science Building Lecture Hall
Thursday, April 17th
12:30 – 1:20 pm

Studies on the biochemical and molecular mechanisms of thiourea mediated abiotic stress tolerance inBrassica juncea L.

Salinity and drought are the major abiotic stresses responsible for reducing the crop productivity and hence, worldwide research is focused to develop strategies for enhancing plant stress tolerance. In this context, the present study was initiated to evaluate the ameliorative potential of thiourea [TU; a non-physiological thiol based ROS scavenger] in Brassica juncea under salt and PEG stress. The entire study was performed on pot experiment. The concentration of 175mg/50g soil of NaCl, 1g/50g of soil of PEG (and 50mg/50g of soil thiourea was used throughout the experiment. The analyses were performed at two developmental stages viz. at seedling (1, 2 and 3 d after stress) and seed soaking (1 and 6 h after stress). In seedlings, thiourea supplementation along with NaCl or PEG stress was found to maintain the reduced redox state, which in turn favored the coordinated action of various enzymatic and non-enzymatic antioxidants and pro-oxidants to reduce the oxidative damage inside the plants. In seeds, thiourea supplementation differentially regulates the expression of a set of genes already known as markers of stress tolerance. The effect of thiourea was also found to be dependent upon ABA and calcium based signaling. Thus, the present study highlights the use of thiourea application as a technology for enhancing NaCl and PEG stress tolerance in Indian mustard.

 

Kuhn Ip
CCIB

Science Building Lecture Hall
Tuesday, April 15th
12:30 – 1:20 pm 

Mathematical Modeling of Bacterial Metabolism

The ubiquity of microbes in our lives has made research into microbial metabolism an important are of study. The biochemical reactions that comprise metabolism determine the consumption and production of chemical compounds and thus, directly relate to efficiency of microbial industrial fermentation. Metabolism and its regulation is also a key determinant in the virulence and survival of pathogenic microbes.

The key to engineering microbial metabolism for a particular purpose is finding targets for manipulation or modification to study experimentally. Microbial metabolism is complex and effects of modifications to a metabolic pathway are not necessarily localized and may be indirect. Trying to study metabolism as a whole entity by investigating all potential sets of modifications experimentally is infeasible. Thus, mathematical models combined with computational search algorithms have been used to ease the experimental burden by directing laboratory efforts towards promising candidates in a systematic and efficient fashion.

Constraint-based modelling, where metabolism is represented as a directed stoichiometric network of constrained biochemical reactions, is one such widely used framework for predicting metabolic phenotype.

Here, we present projects that consider two issues with the application of predictive modelling to metabolic engineering.

First, the complexity of genome-scale metabolic models affects our ability to interpret the predictions generated. A useful tool for understanding and manipulating cellular metabolism is decomposition into elementary flux modes, which systematically organize metabolic networks into potential pathways associated with biochemical functions. Its utility, however, is severely limited since the number of modes increases exponentially with the size of the network. We developed a new method for decomposition that can easily operate on genome-scale metabolic networks. We demonstrated the utility of our method for metabolic engineering of Escherichia coli and for understanding the survival of Mycobacterium tuberculosis during infection.

Second, the underlying model must successfully capture the effects of manipulations on the metabolic behavior of an organism. With constraint-based modelling techniques, it is not immediately clear how to model the correct behavior of inserted heterologous genes under artificial control. We developed a modelling method that we call Proportional Flux Forcing (PFF) to model artificially induced enzymatic genes within constraint-based modelling schemes. We applied PFF in conjunction with flux balance analysis-based computational strain optimization to yield non-obvious genetic manipulation strategies that significantly increase free fatty acid production in Escherichia coli with an artificially induced heterologous thioesterase.

 

Martin Golubitsky
Mathematical Biosciences Institute
Ohio State University

Science Building Lecture Hall
Thursday, March 27th
12:30 – 1:20 pm

Patterns of Synchrony: From Animal Gaits to Binocular Rivalry

This talk will discuss previous work on quadrupedal gaits and recent work on a generalized model for binocular rivalry proposed by Hugh Wilson. Both applications show how rigid phase-shift synchrony in periodic solutions of coupled systems of differential equations can help understand high level collective behavior in the nervous system.  For gaits the symmetries predict unexpected gaits and for binocular rivalry the symmetries predict unexpected percepts.

 

Elizabeth Demaray

TBA

Floraborgs, Victimless Leather: Work Samples From the Field of Art and Science Collaboration

Prof. Elizabeth Demaray manufactures alternative forms of housing for hermit crabs, cultures lichen on the sides of skyscrapers in New York City and, with the engineer Dr. Qingze Zou, is currently building the IndaPlant Project: An Act of Trans-Species Giving in which light-sensing robotic floraborgs allow houseplants to roam freely in a domestic environment, in search of sunlight. Demaray will present her work along with a brief overview of other artwork currently being made in the field of art and science collaboration. This emerging field of practice creates opportunities to heighten scientific literacy in the general public while illuminating the research of individual scientists. Demaray will additionally addresses the challenges and rewards inherent in soliciting institutional support, dealing with the media and presenting work in this genre of art making.

 

Joanna Slusky

Science Building Lecture Hall
Tuesday, March 11th
12:30 – 1:20 pm

The Ins and Outs of Membrane Proteins

Membrane proteins comprise 30% of all proteins and are the majority of modern drug targets. My talk will span both the inner and outer membrane and will use methodologies ranging from molecular biology to protein design to bioinformatics. I will discuss I) how charge affects membrane protein insertion and topology in the inner membrane, II) the relative forces responsible for membrane protein-protein interactions, and III) how charge location clarifies a mechanism for protein insertion in the outer membrane.

 

Christopher C Govern
Postdoctoral Researcher
FOM Institute AMOLF Amsterdam, NL

Science Building Lecture Hall
Monday, March 10th
12:20 – 1:10 pm

Fundamental limits on the precision of cellular sensing 

Cells can sense the concentrations of chemicals in their environments with remarkable precision, rivaling the sensory abilities of the best machines that humans build. Yet, they are built very differently than typical machines, with complex networks of molecular interactions and considerable noise in their outputs.  While much is known about sensory machines in general, we do not understand how cells actually build them out of molecular components or the design constraints cells face in doing so.  I first discuss how common signaling motifs affect the precision of cellular sensing, leading to the specific motifs that can achieve fundamental sensing limits.  I then consider design trade-offs that emerge between the performance of these networks and the resources required to build and operate them at the molecular level, like energy (fuel), copies of signaling proteins, and signal processing time.

 

Amin S. Ghabrial
Dept of Cell and Developmental Biology
University of Pennsylvania
School of Medicine

Science Building Lecture Hall
Thursday, March 6th
12:30 – 1:20 pm

“Tube morphogenesis”

 

 

Buz Barstow

Science Building Lecture Hall
Tuesday, March 4th
12:30 – 1:20 pm

Understanding the Bridge Between Renewable Electricity and Biological Metabolism

Electrosynthesis is a new approach to the production of renewable fuels and chemicals that combines the energy capture efficiency of renewable electricity with the metabolic versatility of biology. Naturally occurring electroactive microbes, that in the wild participate in the geochemical cycling of metals, provide the biological foundation for the uptake of renewable electricity into metabolism. However, despite recent advances, very few of these microorganisms, and others that offer unique capabilities to synthetic biology, can be easily genetically engineered and the systems biology of their unique behavior remains poorly understood. In this talk, I will describe the use of novel high-throughput genetic screens and sequencing methods to discover genes and molecular pathways that underly electron uptake in the model electroactive organism Shewanella oneidensis MR-1.

 

Vyacheslav Labunskyy

Science Building Lecture Hall
Thursday, February 27th
12:30 – 1:20 pm

New insights into translational regulation by the unfolded protein response and its role in aging revealed by ribosome profiling

Impaired protein function caused by protein misfolding and aggregation has been implicated in the development of age-related diseases and regulation of lifespan. Accumulation of misfolded proteins in the endoplasmic reticulum, a cellular organelle responsible for protein folding and trafficking, activates protective signaling pathways that restore protein homeostasis. One such conserved signaling pathway is mediated by the protein misfolding sensor Ire1p and the transcription factor Hac1p, which up-regulate endoplasmic reticulum chaperones, oxidative folding components and factors that facilitate degradation of misfolded proteins to alleviate increased protein folding demand. Here, we describe the role of the unfolded protein response (UPR) signaling pathway and its downstream targets in regulation of lifespan in yeast. While the loss of Ire1p itself had little effect on lifespan, we found that selective inactivation of the individual protein folding and maturation factors led to increased longevity. We also provide evidence that this increased longevity depends on functional Ire1p and is associated with constitutive activation of upstream UPR signaling. We applied RNA-seq and ribosome profiling coupled with next generation sequencing to elucidate the mechanism by which the UPR regulates longevity. Ribosome profiling is based on deep sequencing of ribosome-protected mRNA fragments and provides quantitative information on translation at the genome-wide level. Using this method, we performed detailed characterization of translational changes that are associated with increased UPR activity and identified a set of stress response factors up-regulated in the long-lived mutants. In addition to activation of known UPR targets, we observed induction of other cytoprotective pathways that result in resistance of cells to multiple stresses. These findings establish a novel role for UPR in multiple stress resistance and identify a signaling network that couples stress resistance to longevity.

 

Dr. Orly Levitan
Environmental Biophysics and Molecular Ecology Program,
Institute of Marine and Coastal Sciences,
Rutgers University, New Brunswick

Science Building Lecture Hall
Tuesday, February 25th
12:30 – 1:20 pm

The Intelligent Design of Algal Biofuels

Although marine microalgae account for <1% of the photosynthetic biomass they account for > 45% of the global primary production. Over geological time scales, ca. 10-4 to 10-5 % of their organic carbon becomes incorporated into petroleum reservoirs. Each year, humans extract ~1 million years worth of accumulated oil, leading not only to an inevitable depletion of the reservoirs but to a massive increase in atmospheric CO2. Owing to their high productivity-to-biomass ratio, algae have been long considered as leading  candidates for biodiesel feedstock. Indeed, lipids derived from fossils of a specific algal taxon, the diatoms, are a major component of the highest quality petroleum. Diatoms are an extremely successful taxon in the contemporary oceans and accumulate triacylglycerols (TAG) as storage lipids. In the late 1990’s, genetic tools were developed for diatoms, and several fully sequenced genomes are now available in the public domain with more in the pipeline. These tools have enabled us to use diatoms as a platform for developing high lipid producing cells using a synthetic biological approach.

Using biochemistry, molecular biology, physiology, and biophysical tools, I took an integrative approach to understand the ‘carbon decision tree’ of the model diatom, Phaeodactylum tricornutum, and to denote several potential regulatory nodes that could alter its cellular carbon and energy allocation. Transcriptomic analysis revealed key pathways involved in the remodeling of intermediary metabolism of carbon and nitrogen that allow for the increase in lipid production. I have used molecular and advances transformation tools, to generate several knock-down (RNAi approach) and over-expression plasmids and target some of the postulated regulatory nodes of the central carbon and nitrogen metabolic pathways. The results have led to new cell lines with increased lipid production. An integrative analysis of the transformants indicates that manipulation of the diatom’s cellular carbon flow could be achieved by modification of the nitrogen assimilation pathway, TAG biosynthesis, and by overexpression of specific transcription factors. To displace the total U.S. consumption of fossil fuels, algae must be grown at a scale that yields approximately 20 million barrels of oil per day. Based on my work, I propose that by using genetically engineered diatoms as a platform, it is possible to achieve annual lipid yields that will enable the production of economically viable and environmentally sustainable biofuels for the transportation sector of the economy.

 

Abid Saleem
“Localization of Brain Bio-Iodine”

&

Scott Davis
“Starflag”

Science Building Lecture Hall
Thursday, February 20th
12:30 – 1:20 pm

 

CCIB Qualifying Exam
Thesis Director: Dr Hao Zhu

Marlene Kim

Science Building
Chem Conference Room – 114C
Wednesday, February 19th
10am

PROFILING ENVIRONMENTAL CHEMICALS THAT INDUCE THE ANTIOXIDANT RESPONSE ELEMENT (ARE) SIGNALING PATHWAY USING A NOVEL QUANTITATIVE STRUCTURE IN VITRO-IN VIVO RELATIONSHIP (QSIIR) APPROACH

Oxidative stress causes cell damage which can lead to a variety of neurodegenerative diseases. Reactive oxygen species (ROS) that cause oxidative stress can trigger the transcription of antioxidative enzymes found in the antioxidant response element (ARE) signaling pathway. This pathway is essential for alleviating cell injury, but the mechanisms that lead to cytotoxicity and animal toxicity are still unclear. Previously, a cell-based ARE beta-lactamase reporter gene assay was used to screen over 2,800 compounds from the National Toxicology Program (NTP) and Environmental Protection Agency (EPA) libraries in a Quantitative High Throughput Screening (qHTS) format in efforts to evaluate environmental chemicals that activate the ARE pathway. These compounds were identified and used to develop predictive ARE models using Quantitative Structure-Activity Relationship (QSAR) approaches. The resulting models can be used to virtually screen other compounds of interest (e.g. Tox21 chemical library). Unfortunately, most QSAR models cannot be used to predict animal toxicity. Therefore, we hope to improve the current QSAR models by incorporating more biological information, especially in vitro information, to solve this problem. The integration of chemical and biological information will be used to develop Quantitative Structure In Vitro-In Vivo Relationship (QSIIR) approaches. The in vitro and in vivo relationships established in this step could be used to develop predictive models for complicated animal toxicity endpoints (e.g. neurotoxicity). Furthermore, the final alternative computational toxicity predictors could be used to prioritize potentially toxic compounds, that induce the ARE pathway, for experimental animal tests.

 

Joanna Slusky

Science Building Lecture Hall
Thursday, February 13th
12:30 – 1:20 pm

The Ins and Outs of Membrane Proteins

Membrane proteins comprise 30% of all proteins and are the majority of modern drug targets. My talk will span both the inner and outer membrane and will use methodologies ranging from molecular biology to protein design to bioinformatics. I will discuss I) how charge affects membrane protein insertion and topology in the inner membrane, II) the relative forces responsible for membrane protein-protein interactions, and III) how charge location clarifies a mechanism for protein insertion in the outer membrane.

 

Dr. Kevin Chen
BioMaPS Institute for Quantitative Biology
Department of Genetics
Rutgers University, NB

Science Lecture Hall, Science Building
Tuesday, February 11th
12:30 – 1:20 pm

Spectral Learning of Hidden Markov Models for Genomic Segmentation

Since 93% of disease-related variants in the human genome reside outside of protein coding genes, it is important to develop computational techniques to predict which of these variants are most likely to be causal for the disease. Our group mainly uses computational techniques to interpret variation in the genome that affects the function of non-coding RNAs and gene regulatory elements. In this talk, I will describe our recent results on extending and implementing a novel class of spectral learning algorithms for Hidden Markov Models and related graphical models, with the goal of segmenting the genome into distinct chromatin.

 

Ruchi Lohia

Science Building Lecture Hall
Thursday, February 6th
12:30 – 1:20 pm

Prediction of the effects of the Val66Met polymorphism on the conformational ensemble of an intrinsically disordered protein, Brain-Derived Neurotrophic Factor

The discovery of Intrinsically Disordered Proteins (IDP) has challenged the structure-function paradigm and forced us to find new ways for identifying functional mechanisms of proteins. Studies show that IDPs can function while being partly disordered or may fold once they bind to their receptors. Disease-associated Single Nucleotide Polymorphisms (SNP) are common in the disordered regions of proteins, but not much is known about their effect on the protein structure. Brain Derived Neurotrophic Factor (BDNF) belongs to the family of neurotrophins, and facilitates neurogenesis in its short (mature) form but apoptosis in its long (pro) form. A common (found in 4% of the United States population) SNP that results in the Val66Met mutation in the disordered N terminus domain of the long form of BDNF (proBDNF) has been associated with various neuropsychiatric disorders such as bipolar disorder and Parkinson’s and Alzheimer’s diseases. In order to explore the effect of this SNP on protein structure and dynamics, we conducted Molecular dynamics simulations to identify the effect of the above SNP on likely conformations of proBDNF. Although IDPs have been identified to change their conformations rapidly, many also exhibit some residual secondary structure, which might be biased towards the bound conformation. To construct the ensemble of proBDNF in both forms, large-scale fully atomistic replica exchange calculations of both the Val and Met forms of proBDNF were carried out. We find significant differences in the secondary structure available to Val and Met forms of the protein in the region surrounding the SNP, with results that agree with recent NMR studies. This suggests a position specific residue-type dependence of the residual secondary structure of proBDNF, which might account for functional compromise.

 

Dr. Darius Balciunas
Department of Biology
Temple University

Science Lecture Hall, Science Building
Tuesday, February 4th
12:30 – 1:20 pm

Conditional gene traps for genetic analysis of regeneration in zebrafish

Regeneration is one of the most fascinating and biomedically relevant biological processes. Studies implicating classical developmental pathways- Wnt, Fgf, Bmp and retinoic acid- in regeneration underscore the overlap between genetic control of development and regeneration, necessitating the use of conditional mutants to study regeneration. However, conditional mutants are only readily generated in the mouse, which has rather poor regenerative capacity. Conversely, in vertebrate model systems with extensive regenerative capacity, such as the zebrafish, very few conditional mutants exist. To address this chiasmus in regeneration biology, we have constructed a fully conditional gene trap vector for use in zebrafish. Several mutants affecting development of the cardiovascular system have been recovered from our pilot screens, including an insertional allele of tbx5a. Our data indicate that in addition to playing an essential role in pectoral fin and heart development, tbx5a plays an essential role in cardiac regeneration. Our future studies will focus on thorough characterization of regeneration defect in tbx5a mutants, while also testing regenerative capacity of other conditional cardiovascular mutants.

 

Kyle Jenkins

Science Building Lecture Hall
Thursday, January 30th
12:30 – 1:20 pm

Biomusicology: An Interdisciplinary Look at the Crossroads of Science and Art

 

Zhijun Li, Ph.D. 

Faculty Lounge, Armitage Hall
Tuesday, January 28th
12:30 – 1:20 pm

Three-dimensional Structure Modeling of Transmembrane Proteins

Transmembrane proteins account for 30% of the human genome and are important drug targets. Elucidating the three-dimensional structures of membrane proteins is crucial to understanding their structure-function relationships and to their structure-based drug design. In disparity to their biological significance, the structure of most membrane proteins remains unknown, comprising less than 1% of the total structures in the Protein Data Bank. This is mainly due to the challenge of experimental structure determination of membrane proteins. As a result, computational modeling plays an important role in the studies of membrane proteins and in structure-based drug design efforts targeting these proteins.

In this talk, three ongoing projects from our lab that is related to structure modeling of helical membrane proteins will be presented: (1) Developing an objective measure for quality assessment of membrane protein structures/models through bioinformatics approaches; (2) Developing a computational approach for conformational sampling to improve the standard homology modeling techniques; and (3) Applying computational modeling techniques to the chemoreceptors and their regulatory enzyme. 

Rachel Sohn

Science Lecture Hall, Science Building
Thursday, January 23rd
12:30 – 1:20 pm

Memory Reconsolidation as a Treatment Option for Opioid Dependency

Drug dependency, specifically to opioids, is a detrimental disease which has no known cure at the current time. Research has shown that abnormalities within the mesolimbic pathway in the brain can account for the negative behaviors associated with users. Posttraumatic stress disorder is another malady that is affected by the mesolimbic pathway, specifically to anomalies in the amygdala. By further researching this pathway, more conclusions can be drawn and pharmacological ways of treating the disease can be developed. Recent studies have focused on memory reconsolidation, a process of recalling memories and altering them. Using propranolol and clonidine, patients with PTSD showed great improvement in their quality of life as well as displayed minimal symptoms. Although not yet proven, this technique could be applied to those who are opioid dependent as a way to eliminate the triggering memories that cause a patient to relapse.

Dr. Bing Yan
School of Chemistry and Chemical Engineering
Shangdong University, China

Thursday, November 7th, 2013
12:30pm – 1:20pm
Faculty Lounge, Armitage Hall

Modulation of the Biological Activities of Nanoparticles

Nanomaterials are widely used in various industrial sectors, biomedicine, and more than 1300 consumer products. Although there is still no unified safety regulation, their potential toxicity is a major concern worldwide. We discovered that nanoparticles target and enter human cells, perturb cellular signaling pathways, affect various cell functions, and cause malfunctions in animals. Because the majority of atoms in nanoparticles are on the surface, chemistry modification on their surface may change its biological properties significantly. We modified nanoparticle surface using a nano-combinatorial chemistry approach. Novel nanoparticles were discovered to possess reduced toxicity, enhanced cancer targeting ability, or increased cell differentiation regulation. Quantitative nanostructure-activity relationships (QNAR) models have been built and applied for predicting biocompatible nanoparticles.

Sulbha Choudhari
Center for Computational & Integrative Biology
Rutgers University-Camden

Thursday, October 31st, 2013
12:30pm – 1:20pm
Science Building, Lecture Hall 

Insights into Glacial Ecosystem using Metagenomics

The temperature in the Arctic region has been increasing in the recent past accompanied by melting of its glaciers. We took a snapshot of the current microbial inhabitation of an Alaskan glacier (which can be considered as one of the simplest possible ecosystems) by using metagenomic sequencing of 16S rRNA recovered from ice/snow samples. Somewhat contrary to our expectations and earlier estimates, a rich and diverse microbial population of more than 2,500 species was revealed including several species of Archaea that has been identified for the first time in the glaciers of the Northern hemisphere. The most prominent bacterial groups found were Proteobacteria, Bacteroidetes, and Firmicutes. Firmicutes were not reported in large numbers in a previously studied Alpine glacier but were dominant in an Antarctic subglacial lake. Principal component analysis of nucleotide word frequency revealed distinct sequence clusters for different taxonomic groups in the Alaskan glacier community and separate clusters for the glacial communities from other regions of the world. Comparative analysis of the community composition and bacterial diversity present in the Byron glacier in Alaska with other environments showed larger overlap with an arctic soil than with a high arctic lake, indicating patterns of community exchange and suggesting that these bacteria may play an important role in soil development during glacial retreat.

William J. Welsh, Ph.D.
N. H. Edelman Professor in Bioinformatics
Department of Pharmacology
Rutgers University
Robert Wood Johnson Medical School

Tuesday, October 29th, 2013
12:30pm – 1:20pm
Faculty Lounge, Armitage Hall

Computational Approaches to Accelerate Drug Discovery

The recent emergence of the translational medicine paradigm has imposed a high premium on advanced computational platforms to accelerate the discovery of new diagnostic and therapeutic agents. We thus introduce two computational tools, Shape Signatures and Avalanche, developed in the Welsh laboratory that offer a central portal for drug discovery, virtual screening of chemical libraries, and predictive toxicology. Among their many attractive features, Shape Signatures and Avalanche are extremely fast, are accessible via a user-friendly GUI, and can handle any number and type of molecular species. Our current Shape Signatures and Avalanche chemical databases comprise over 3 million commercially available organic compounds including natural products and FDA-approved small molecule drugs. I will present Case Studies, taken from my research laboratory, to demonstrate the utility of Shape Signatures and Avalanche within an integrated drug discovery project. Examples will be drawn from projects aimed at the discovery of novel treatments for cancer, pain, and infectious, as well as cosmetic agents.

Dr. Wei Xu
Department of Oncology
McArdle Laboratory for Cancer Research
University of Wisconsin

Thursday, October 24th, 2013
12:30pm – 1:20pm
Lecture Hall, Science Building

Developing in vitro and in vivo models for probing environmental estrogens’ action via estrogen receptor dimers

Many environmental estrogens so called xenoestrogens mimic the action of endogenous estrogens to regulate the risk of breast cancer. The effects of xenoestrogens are mediated by functional estrogen receptor dimers. Although numerous biochemical evidence exist in support of ERa/b heterodimer formation, the functions of heterodimers were completely unknown.

We have developed Bioluminescence Resonance Energy Transfer (BRET) assay to study intermolecular interactions of ERa/b heterodimers. Further, this assay was used for high throughput screening and identified several ERa/b heterodimer inducing compounds.

These compounds allow us to reveal the growth inhibitory function of ERa/b heterodimers and in silico modeling identifies possible pharmacophore conferring ERa/b selectivity. Finally, I will discuss recent animal models developed to screen ligands specific to ERa and ERb in vivo.

Ammar Naqvi
Rutgers University-Camden

Thursday, October 17, 2013
12:30 – 1:20 pm
Science Lecture Hall, Science Building

Patterns of microRNA changes in Aging and Neurodegeneration

microRNAs (miRNAs) are 20~24nt small RNAs that impact a variety of biological processes, from development to age-associated events. To study the role of miRNAs in aging, studies have profiled the levels of miRNAs with time. However, evidence suggests that miRNAs show heterogeneity in length and sequences in different biological contexts. Here, by examining the expression pattern of miRNAs by northern blot analysis, we found that Drosophila miRNAs show distinct isoform pattern changes with age. Surprisingly, an increase of some miRNAs reflects increased 2′-O-methylation of select isoforms. Small RNA deep-sequencing revealed a global increase of miRNAs loaded into Ago2, but not into Ago1, with age. In addition, only specific miRNA isoforms showed increased loading into Ago2, but not Ago1, indicating a mechanism for differential loading of miRNAs between Ago1 and Ago2 with age. Mutations in Hen1 and Ago2, which lack 2′-O-methylation of miRNAs, result in accelerated neurodegeneration and shorter lifespan, suggesting an impact of the age-associated increase of 2′-O-methylation of small RNAs on age-associated processes. Our study highlights that miRNA 2′-O-methylation at the 3′end is modulated by differential partitioning of miRNAs between Ago1 and Ago2 with age, and that this process might impact age-associated processes in Drosophila.

Dr. Paolo Zunino
Department of Mechanical Engineering and Materials Science
University of Pittsburgh

Thursday, October 10th, 2013
12:30pm – 1:20pm
Lecture Hall, Science Building 

Computational models for fluid and chemical exchange between microcirculation and tissue interstitium

Reduced models of fluid flow or mass transport in heterogeneous media are often adopted in the computational approach when the geometrical configuration of the system at hand is too complex. A paradigmatic example in this respect is blood flow through a network of capillaries surrounded by a porous interstitium. We numerically address this biological system by a computational model based on the Immersed Boundary Method (IBM), a technique originally proposed for the solution of complex fluid-structure interaction problems. Exploiting the large aspect ratio of the system, we avoid resolving the complex 3D geometry of the submerged vessels by representing them with a 1D geometrical description of their centerline and the resulting network [1,2].

Cancer employs mass transport as a fundamental mechanism of coordination and communication and the physics of mass transport within body compartments and across biological barriers differentiates cancer from healthy tissues [3]. Mass transport is also at the basis of cancer pharmacological treatment Delivery of diagnostic and therapeutic agents differs dramatically between tumor and normal tissues. In contrast to healthy tissue, tumors exhibit interstitial hypertension, which is caused by the high permeability of tumor vessels in combination with the lack of functional lymphatic vessels in the tumor interstitial space.

The analysis of fluid and chemicals exchange in vascularized tumors is a relevant application of the model proposed here. We will use it to study fluid and mass exchange between the capillaries and the interstitial volume, as well as to compare different modalities to deliver chemotherapy drugs to the tumor mass, including using nanoparticles as delivery vectors.

[1] D’Angelo, C., Quarteroni, A. On the coupling of 1D and 3D diffusion-reaction equations. Application to tissue perfusion problems (2008) Mathematical Models and Methods in Applied Sciences, 18 (8), pp. 1481-1504.
[2] L.Cattaneo, P.Zunino, Computational models for fluid exchange between microcirculation and tissue interstitium. Networks and Heterogeneous Media (2013). MOX Report 25/2013
[3] Baxter, L.T., Jain, R.K. Transport of fluid and macromolecules in tumors. I. Role of interstitial pressure and convection (1989) Microvascular Research, 37 (1), pp. 77-104. 

Dr. Laura Scheinfeldt
Coriell Institute for Medical Research
Coriell Personalized Medicine Collaborative

Thursday, September 26th, 2013
12:30pm – 1:20pm
Lecture Hall, Science Building

An integrated genomic approach to the study of human adaptation to high altitude

The recent availability of genomic data and related methodologies has resulted in several genome-wide studies of human adaptation across geographically diverse populations. Such studies have provided novel candidate genes and pathways putatively involved in adaptation to different environments, and in particular, to high altitude. However, one of the limitations of these studies is the high false positive rate for candidate loci, and additional work is needed to translate the strongest results into biologically interpretable adaptive candidate variants. I will discuss methods that may help to recover biological signals of adaptation to high altitude in Ethiopia and ways in which I have incorporated complementary phenotypic data. I will also present results from studies of other high altitude regions across the world and discuss the combined findings.

Dr. Eric Klein
Dept. of Biology
Rutgers University-Camden

Tuesday, September 24th, 2013
12:30pm – 1:20pm

Mechanical signaling pathways in bacteria

The dynamic regulation of virulence is an essential aspect of pathogenesis that holds great promise for combating infectious disease.  While the overwhelming emphasis of the field to date has been on the chemical cues that mediate bacteria-host interactions, there is evidence indicating that bacteria can also sense and respond to their mechanical environment.  In particular, I have demonstrated that uropathogenic Escherichia coli (UPEC) induce a novel gene expression program in response to adhesion to stiff surfaces.  While the mechanism by which fimbriae attach to their targets is well understood, little is known about how fimbrial attachment may trigger pathogenic gene expression.  Using a variety of genetic and microscopy-based approaches, my work will focus on how mechanical forces stimulate adhesion-mediated gene expression, the mechanism of bacterial mechanotransduction, and the role of mechanical signaling in pathogenic infection.  Ultimately, my goal is to identify components of the mechanotransduction pathway as targets for the development of novel therapeutics for use as alternatives to traditional antibiotics.

Dr. Luca Larini
Dept. of Physics
Rutgers University-Camden

Thursday, September 19th, 2013
12:30pm – 1:20pm
Lecture Hall, Science Building 

Bridging length and time scales in complex materials

Complex systems (such as biomolecules or glasses) are characterized by multiple time and length scales that are associated with different properties of the system under examination. As a consequence, simplified models (referred to as coarse-grained models) can be constructed that retain only the most relevant physical properties at a given scale. These models can be expected to render both theory and simulations more tractable. In this talk I will present examples of successful coarse-grained models and techniques applied to glass transition, biomolecules and simple liquids. These examples will be used to introduce basic notions of the theory and the algorithms employed in multiscale modeling.

Dr. Jinglin Fu
Dept. of Chemistry
Rutgers University-Camden 

Tuesday, September 17th, 2013
12:30pm – 1:20pm
Faculty Lounge, Armitage Hall

Spatially Interactive Biomolecular Networks Organized by Nucleic Acid Nanostructures

The cellular activities of all organisms are governed by a variety of multi-step chemical conversion events, or biochemical pathways that exhibit extraordinary yield and specificity. Biological systems have evolved numerous mechanisms to regulate this process including molecular scaffolding and spatial confinement, where the function of a pathway is critically dependent on the relative position, orientation, and quantity of participating enzymes. Understanding the effect of spatial arrangement on pathway activity in multi-enzyme systems will not only advance our knowledge of fundamental biomolecule networks, but is also important to translate biochemical reaction pathways to non-cellular environment applications. Toward this goal, DNA nanostructures, that pieces of DNA can come together and spontaneously assemble into sophisticated structures, have been employed as assembly scaffolds to organize multiple enzymes with precisely-controlled spatial positions and orientation. This makes it possible to investigate and mimic several important mechanisms for multi-enzyme pathways, including the dependence of the distance between the enzymes on the overall reaction rate and specificity

(Fig.1A), the ‘Swing Arm’-organized substrate channeling (Fig.1B) and the regulatory enzymatic circuitry (Fig.1C). These approaches and principles provide a predictable framework to create efficient and regulatory nanoscale catalytic complexes, which will find utility in the development of the catalysts for chemical synthesis, bioenergy, diagnostic and therapeutic applications.

 

 

 


2012-2013 Seminars:

Thursday, January 24, 2013, Science Building Lecture Hall
Extracting Essential Features of Biological Signaling Networks
Speaker: Dr Natalie Arkus, Postdoctoral Fellow, Department of Physics and Astronomy, University of Pennsylvania

Abstract: Because biological signaling networks have many components, it has become common to model such networks using large systems of coupled ordinary differential equations.  However, there is as yet no simple way of determining how solutions to large systems depend on their parameters.  In contrast, large systems of differential equations describing electronic circuits are routinely reduced to simpler systems that quantitatively capture circuit behavior using lumped parameters for resistance, capacitance, and inductance.  We show that biological signaling networks can similarly be reduced to systems involving a few equations and effective parameters.  The effective parameters lump the system’s many components together, yielding a simplified system that contains within it information on all of the many components.  We apply this method to a model from the literature of heat shock response in E. coli consisting of 31 equations and 48 parameters.  We reduce this model to just 1 equation and 3 effective parameters. The reduced system quantitatively agrees with the original, and demonstrates that feedback loops do not necessarily confer a faster heat shock response at lower cost, as had been claimed.  We discuss the application of this method to other models from recent literature, such as that of Beta-catenin degradation in the Wnt signaling network – where a model of 19 equations is reduced to 1-3 equations (depending on the initial conditions), and the features that determine the rate of beta-catenin degradation are extracted.

Tuesday, January 29, 2013, Armitage Hall Faculty Lounge
A Control Theory Approach to Engineering Biomolecular Networks
Speaker: Dr Domitillo del Vecchio, W. M. Keck Career Development Professor in Biomedical Engineering, Associate Professor, Laboratory for Information and Decision Systems (LIDS), Department of Mechanical Engineering, MIT

Abstract: The past decade has seen tremendous advances in the fields of Systems and Synthetic Biology to the point that de novo creation of simple biomolecular networks, or “circuits”, in living organisms to control their behavior has become a reality. A near future is envisioned in which re-engineered bacteria will turn waste into energy and kill cancer cells in ill patients. To meet this vision, one key challenge must be tackled, namely designing biomolecular networks that can realize substantially more complex functionalities than those currently available.

A promising approach to analyzing or designing complex networks is to modularly connect simple components whose behavior can be isolated from that of the surrounding modules. The assumption underlying this approach is that the behavior of a component does not change upon interconnection. This is often taken for granted in fields such as electrical engineering, in which insulating amplifiers enforce modular behavior by suppressing impedance effects. This triggers the fundamental question of whether a modular approach is viable in biomolecular circuits. Here, we address this research question and illustrate how, just as in many mechanical, hydraulic, and electrical systems, impedance-like effects are found in biomolecular systems. These effects, which we call retroactivity, dramatically alter the behavior of a component upon interconnection. We illustrate how, similarly to what is performed in electrical networks, one can reduce the description of an arbitrarily complex system by calculating equivalent retroactivities to the input. By merging disturbance rejection and singular perturbation techniques, we provide an approach that exploits the structure of biomolecular networks to design insulating amplifiers, which buffer systems from retroactivity effects. We provide experimental demonstration of our theory on a reconstituted protein modification cycle extracted from bacterial signal transduction and on a synthetic biology circuit in vivo.

Thursday, February 14, 2013, Science Building Lecture Hall
The Tox21 Program
Speaker: Menghang Xia, Ph.D., Group Leader, Cellular Toxicity & Signaling, NIH Chemical Genomics Center

Abstract: To meet the needs of toxicity testing in the 21st century, the National Toxicology Program (NTP), the NIH Chemical Genomics Center (NCGC), the U.S. Environmental Protection Agency (EPA), and the U.S. Food and Drug Administration (FDA) formed the Tox21 partnership. The goals of Tox21 are to identify mechanisms of compound action at the cellular level, prioritize chemicals for further toxicological evaluation, and develop useful predictive models of in vivo biological response. In the presentation, I will describe the Tox21 program, qHTS-based compound testing and the various Tox21 screening assays that have been validated and screened at the NCGC.

Thursday, March 7, 2013, 12:20pm – 1:20pm, Lecture Hall, Science Building 
Patterning challenges for optional sex: the case of reproductive polyphenism in aphids 
Speaker: Dr Gregory Davis, Assistant Professor, Biology, Bryn Mawr College

Abstract: The pea aphid, Acyrthosiphon pisum, exhibits several environmentally cued, discrete, alternate phenotypes (polyphenisms) during its life cycle. In the case of the reproductive polyphenism, differences in day length determine whether mothers will produce daughters that reproduce either sexually by laying fertilized eggs (oviparous sexual reproduction), or asexually by allowing oocytes to complete embryogenesis within the mother without fertilization (viviparous parthenogenesis). Oocytes and embryos that are produced asexually develop more rapidly, are yolk-free, and much smaller than oocytes and embryos that are produced sexually. Perhaps most striking, the process of oocyte differentiation is truncated in the case of asexual/viviparous development, potentially precluding interactions between the oocyte and surrounding follicle cells that might take place during sexual/oviparous development. Given the important patterning roles that oocyte-follicle cell interactions play in Drosophila, these overt differences suggest that there may be underlying differences in the molecular mechanisms of pattern formation. We have found differences in the expression of torso-like, as well as activated MAP kinase, suggesting that there are important differences in the hemipteran version of the terminal patterning system between viviparous and oviparous development. Establishing such differences in the expression of patterning genes between these developmental modes is a first step toward understanding how a single genome manages to direct patterning events in such different embryological contexts.

Wednesday, March 27, 2013, Campus Center Multi-Purpose Room
Fast Algorithms for Brownian Dynamics Simulation with Hydrodynamic Interactions
Speaker: Dr Shidong Jiang, Associate Professor, Department of Mathematical Sciences, New Jersey Institute of Technology

Abstract: In the Brownian dynamics simulation with hydrodynamic interactions, the motion of the Brownian particles can be described via a stochastic differential equation (SDE). The change of the displacement vectors of Brownian particles in the popular Ermak-McCammon algorithm for Brownian dynamics simulation consists of two parts: a deterministic part which is proportional to the product of the Rotne-Prager-Yamakawa (RPY) tensor and the given external forces; and a hydrodynamically correlated random part whose covariance is proportional to the RPY tensor. For an arbitrary N-particle configuration, the computation cost of the classical algorithms for computing the deterministic part is quadratic in N; and the computational cost for generating random vectors with a specific covariance is cubic in N. These form the bottleneck for long term large-scale Brownian dynamic simulation.

In this talk, we will first present two fast multipole methods (FMM) for computing the deterministic part. We then discuss several methods of generating random vectors whose covariance matrix is proportional to the RPY tensor.  The performance of our algorithms will be illustrated via several numerical examples. The algorithms are expected to be useful for the study of diffusion limited reactions, polymer dynamics, protein folding, and particle coagulation.

This is joint work with Zhi Liang at NJIT, Zydrunas Gimbutas & Leslie Greengard at NYU, & Jingfang Huang at UNC at Chapel Hill.

Thursday, March 28, 2013, 12:20pm – 1:20pm, Lecture Hall, Science Building 
Mathematical Models for Cancer Treatments – The Role of the Vasculature and the Immune System in Optimal Protocols for Cancer Therapies 
(joint research with Urszula Ledzewicz, Southern Illinois University) 
Speaker: Dr Heinz Schättler, Dept. of Electrical and Systems Engineering, Washington University, St Louis

Abstract: A systematic study of cancer treatments requires that we take into account not only the tumor and its growth, but also its microenvironment which comprises the cancerous cells, (sensitive and resistant to the treatment), healthy cells, tumor vasculature, immune system and more. In this talk, I will discuss some mathematical models that include increasingly more complex aspects of the tumor microenvironment such as tumor heterogeneity, angiogenic signaling, and tumor immune system interactions. These models will be analyzed from a dynamical systems point of view in the context of the optimal control problem of designing treatment protocols. Using methods of geometric optimal control, syntheses of optimal solutions will be described for some of these models. As more and more aspects of the tumor microenvironment are taken into account, optimal solutions change from bang-bang solutions (which correlate with the standard medical practice of giving chemotherapeutic agents in maximum tolerated doses) to administration schedules that favor singular controls (which administer agents at specific time varying reduced dose rates). This raises the possibility of metronomic administrations of agents (at low concentrations over prolonged periods without any major interruptions), an alternative scheduling approach that has shown some success in pediatric cancers. The talk will also address some of the mathematical challenges that arise in the analysis of these generally highly nonlinear, multi-input control systems. 


2011 – 2012 Seminars:

Monday, December 12, 2011, (BSB 334
Characterization of ultradian rhythms in adult male rats through EEG analyses and in Neuorspora crassa through growth data analyses 
Speaker: Steve Moffett, Ph.D. candidate, CCIB, Rutgers University

Abstract: The brain gives rise to rhythms on different time scales, including circadian or ultradian. In humans, hormone secretion is known to follow an ultradian rhythm of approximately 90 minutes. To date, ultradian rhythms have not been well-characterized in rodents. Adult male rats were prepared with electrodes for electroencephalography (EEG) and in the neck musculature for electromyography. After recovery, the EEG signal was recorded for 48-hours in a 12/12 L/D cycle. Following data acquisition, a window fast-Fourier transform (FFT) of EEG data was computed for 30-second epochs. The percentages of total power in 1-4 Hz, 4-8 Hz, or 1-8 Hz frequency bands were separately plotted by epoch over the course of the study. An ultradian rhythm in percent total power was apparent in the plots for each of the frequency ranges. To quantitate the ultradian rhythm, trained observers independently determined the time of occurrence of local minima in the window FFT plot. The means of measurements of periods between minima for given observers ranged from 9.4 to 13.2 minutes. A similar study was conducted on the growth data of the model circadian organism Neurospora crassa.

February 6, 2012
Systematic Structural Mass Spectrometry: Probing Structures of Membrane Skeletons Using Chemical Crosslinking, Mass Spectrometry and Homology Modeling
Speaker: David W. Speicher, Ph.D., Casper Wistar Professor in Computational and Systems Biology
Director, Center for Systems and Computational Biology, The Wistar Institute

Abstract: Crystallographic and NMR techniques have produced high resolution structures of many protein domains, small proteins and some protein complexes. However, few high resolution structures exist for proteins or protein complexes larger than 100 kDa, and no high resolution structures exist for the majority of proteins expressed by the human genome. A strategy for systematically determining novel protein structures is to use homology modeling since one or more high resolution structures exist for most protein folds. However, major challenges include: distinguishing between multiple plausible models, improving accuracy of predicted models, and experimental validation of models. A few distance constraints from chemical crosslinks, particularly “zero-length” linkers, can effectively address all of these challenges, and recent advances in tandem mass spectrometry (MS/MS) have improved in-depth analysis of complex peptide mixtures. Despite these advances, chemical crosslinkers remain under-utilized because there are no effective software tools for identification of peptides crosslinked by zero-length crosslinkers. While analysis of small proteins and protein complexes can be performed through manual review of the MS/MS data, this approach is very time consuming and tedious for moderate-sized proteins and impractical for large proteins and protein complexes. To address this roadblock, we recently developed software and a multi-tiered MS/MS analysis strategy that eliminates subjective, tedious manual review of MS/MS data, identifies more crosslinks, increases the confidence of crosslink assignments, and enables analysis of much larger proteins and protein complexes. We are applying this strategy to the systematic analysis of spectrin and other protein complexes in the membrane skeleton, a two-dimensional network on the cytoplasmic face of the membrane that provides membrane flexibility and integrity in red cells as well as other cell types. A long term goal is the development of a comprehensive medium resolution structure for the entire red cell membrane skeleton.

March 19, 2012 
What I Saw When I Watched Some Evolution 
Speaker: Dr. Michael Desai, Assistant Professor, Department of Organismic and Evolutionary Biology, Harvard University

Abstract: Evolutionary adaptation proceeds by the accumulation of beneficial mutations. We often think of these beneficial mutations as being rare, and adaptation is then characterized by a sequence of “selective sweeps”: a beneficial mutation occurs, spreads through an entire population, then later another beneficial mutation occurs, and so on. This simple picture is the basis for much of our intuition about adaptive evolution, and underlies a number of practical techniques for analyzing sequence data. Yet many large and mostly asexual populations — including a wide variety of unicellular organisms and viruses — live in a very different world. In these populations, beneficial mutations are common, and frequently interfere or cooperate with one another as they all attempt to sweep simultaneously. This radically changes the way these populations adapt: rather than an orderly sequence of selective sweeps driven by single strongly beneficial mutations, evolution is a constant swarm of competing and interfering mutations. The fate of any individual mutation depends on how it interacts with this background of other variation; no single mutation drives adaptation by itself. I will describe a new experimental system developed to directly visualize some aspects of these dynamics, and describe the results of 1000 generations of experimental evolution of 600 budding yeast populations. We see intriguing signatures of complicated patterns of interference between mutations, as well as the unexpected spontaneous evolution of stable polymorphisms in some populations. I will describe some further experiments to show how this dynamics depends on factors such as population subdivision and patterns of epistasis. If time allows I will also describe new theoretical work which predicts how many beneficial mutations collectively lead to variation in fitness within the population, and how each mutation interacts with this variation to determine its ultimate fate.  

April 9, 2012 
Automated Annotation of Chemical Names in the Literature
Speaker: Jun Zhang, PhD, Post-doc with Hao Zhu, Assistant Professor, Chemistry, Rutgers-Camden

Abstract: A significant portion of the biomedical and chemical literature refers to small molecules. The accurate identification and annotation of compound name that are relevant to the topic of the given literature can establish links between scientific publications and various chemical and life science databases. Manual annotation is the preferred method for these works because well-trained indexers can understand the paper topics as well as recognize key terms. However, considering the hundreds of thousands of new papers published annually, an automatic annotation system with high precision and relevance can be a useful complement to manual annotation. An automated chemical name annotation system, MeSH Automated Annotations (MAA), was developed to annotate small molecule names in scientific abstracts with tunable accuracy. This system aims to reproduce the MeSH term annotations on biomedical and chemical literature that would be created by indexers. To reduce the false-positive annotations, MAA incorporated several filters to remove “incorrect” annotations caused by nonspecific, partial, and low relevance chemical names. Accurate chemical name annotation can help researchers not only identify important chemical names in abstracts, but also match unindexed and unstructured abstracts to chemical records. The current work is tested against MEDLINE, but the algorithm is not specific to this corpus and it is possible that the algorithm can be applied to papers from chemical physics, material, polymer and environmental science, as well as patents, biological assay descriptions and other textual data.  

Monday, April 23, 2012, 12:10 – 1:10 pm, BSB 117 
Modeling and simulations of single-stranded RNA viruses 
Speaker: Mustafa Burak Boz, Georgia Institute of Technology, Ph.D. Candidate in Physical Chemistry

Abstract: We investigate the assembly of Satellite Tobacco Mosaic Virus (STMV) using coarse-grained models. We use multi-level coarse-grained representations to decrease the computational expenses and adequately represent the different parts of the viral structure. The RNA coarse-grained model is generated from a proposed secondary structure [1]. The RNA model has one pseudo-atom (bead) per residue. The coarse-grained model for the capsid contains twenty triangular units, each of which also contains three flexible positively charged protein tails. The assembly process as well as the stability of the virus mainly depends on RNA-protein and protein-protein interactions. The protein tails are attracted to the RNA by electrostatic interactions while the capsid proteins are weakly attracted with each other by hydrophobic interactions. We model RNA-protein interactions with a Debye-HÃŒckel potential and protein-protein interaction with a Lennard-Jones potential. We vary values of these two interactions to find regions where the virus is stable and will self-assemble. Finally, we investigate the assembly of the virus using molecular dynamics. These simulations help us understand the individual roles of these two interactions on viral assembly. 

Ref: 1. Schroeder JS, Stone, WJ et.al. Biophysical Journal,101: p. 167-175, 2011  

Thursday, April 26, 2012, 12:30 – 1:30 pm, Science Bldg, Science Lecture Hall 
Investigating functional roles of circadian rhythms in Neurospora crassa employing mathematical modeling and experimental validations
Speaker: Christian Hong, PhD, Assistant Professor, The Department of Molecular & Cellular Physiology, University of Cincinnati

Abstract: Fundamental cellular processes that maintain most organisms’ health and survival include cell cycle, DNA damage response, and circadian rhythms. Cell cycle is equipped with multiple checkpoints for controlled growth, DNA rep-lication, and divisions. DNA damage response (DDR) mechanisms control cell fate by either repairing single or double strand breaks, or triggering apoptosis for programmed cell death when the damage is fatal. Last, but not least, is circadian rhythm that keeps track of time of a day, and plays a central role in most organ-isms for setting the sleep/wake cycle, feeding rhythms, and other daily activities. These distinct molecular mechanisms communicate with each other and create a complex bio-molecular network to optimize conditions for cells to grow and adapt to the surrounding environment. We explore functional roles of circadian rhythms in other cellular processes such as cell cycle employing mathematical modeling and experimental validations using a modeling organism Neurospora crassa.  

Monday, April 30, 2012, 12:10 – 1:10 pm 
Immune-based identification of drug resistance in  Mycobacterium tuberculosis: Shifting a paradigm or tilting at windmills? 
Speaker: Gregory P. Bisson, MD, MSCE, Assistant Professor of Medicine and Epidemiology, Division of Infectious Diseases, Senior Scholar, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine

Abstract: Nearly 2 billion people, one third of the World’s population, are at risk of active tuberculosis (TB) because they are latently infected with the causative agent Mycobacterium tuberculosis ( Mtb ) , and almost 2 million TB-related deaths occur annually. A major barrier to TB control is that detection of Mtb drug resistance requires collection of microbiological samples, which are not available in many cases of active disease and in all cases of latent infection. Treatment of latent  Mtb  infection, a necessary approach to global TB control efforts, cannot be properly targeted if drug resistance is suspected, which represents a major knowledge gap. A central tenet of microbiology and infectious diseases holds that identification of antibiotic resistance in human pathogens requires direct access to the organism. In this talk, the hypothesis that the host adaptive cellular immune system responds to changes in the proteome of pathogens that specifically occur as a result of genetic mutation(s) conferring drug resistance will be presented, using rpoB mutation and rifampicin resistance in  Mtb   as an example.  The host immune system is not expected to consistently and specifically recognize epitope differences conferred by SNPs in rpoB , but data from model organisms phylogenetically related to Mtb indicate that rpoB mutation activates dormant gene networks not expressed by wild-type strains. The possibility that Mtb strains share conserved, ancestral responses of competition interference will be considered in light of preliminary proteomics data, and the public health implications of the approach will be discussed 

Thursday, June 21, 2012, 1:00pm – 2:00pm, Campus Center – South BC Conference Room 
Information Session on Entrepreneurial Collaborations 
Speaker: CCIB member faculty in conjunction with several faculty members of the School of Business

Abstract: The CCIB, in conjunction with several faculty members of the School of Business, is sponsoring a one-hour session to address possible collaborations on entrepreneurial endeavors, start-ups, etc., as well as the potential for related graduate course offerings and seminars. All interested parties are welcome to attend. 
The format for the meeting would be an initial general conversation on programmatic collaborations. This will be followed by a series of 5-10 minute presentations on projects of CCIB researchers and discussions with the members of the Business School on potential entrepreneurial ventures related to the research. Please reply to Karen Taylor at kdt41@camden.rutgers.edu if you would like to make a research presentation at the meeting. RSVP is requested via email to karen if you plan to attend. Thank you. 

Monday, June 25, 2012 
The Defence Science and Technology Organisation (DSTO) is part of Australia’s Department of Defence and Australian Government’s lead agency charged with applying science and technology to protect and defend Australia and its national interests ( http://www.dsto.defence.gov.au ). 
Speaker: Dr Gulay Mann BSc (Hons), Ph.D., Research Advisor to Defence Science Institute, Principal Research Scientist, Human Protection & Performance Division, Defence Science and Technology Organisation, Australia.

Abstract: In January 2002, Dr Mann commenced work with CSIRO Division of Plant Industry at the Black Mountain laboratories in Canberra. Her research activities included: a) The application of molecular/genetic analyses to investigate the genes responsible for complex dough attributes; b) Processing of novel cereal grains for maximum health benefit; c) Genetic basis of wheat quality; d) Development of improved analytical methods for key wheat quality traits; and e) Development of a laboratory scale baking facility. She has written numerous papers and conference proceedings on dough rheology, wheat and end product quality.
Dr Mann joined DSTO’ss Human Protection and Performance Division in February 2006 as an S&T 7 (corresponding to Principal Research Scientist), as Capability Leader of Defence Nutrition and Food Technology. Dr Mann provided scientific leadership for DSTO’ss research programs in Nutrition & Dietetics and Food Science & Technology, and also supervised the management of the freeze dried meal production line. 
In March 2009, Dr Mann took up a career development position at the DSTO Headquarters as the Director Strategic Planning and Coordination in Science Strategy and Policy Branch. In this role, she involved in the strategic coordination and science planning across DSTO as well as providing policy advice on the defence science and technology capabilities needed to achieve Defence’s broad objectives and priorities.
Since September 2011, Dr Mann is developing an enabling research program in Synthetic Biology.